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• Validation_for_human_early_embryonic_substitutions_

  PCR and MiSeq validation for early embryonic substitution candidates from 400 Breast cancer patients

  Study EGAS00001001218

• Acute myeloid leukemia sequencing data

  This study contains tumor DNA and RNA sequencing data for 1 AML patient

  Study EGAS00001006354

• Array data for oesophageal and related samples - aks_paper_methyl_barretts_release

  Array data for oesophageal and related samples - aks_paper_methyl_barretts_release

  Dataset EGAD00010001972

• Dataset for "Intratumoral Heterogeneity and Clonal Evolution Induced by HPV Integration" (pacBio)

  Dataset for "Intratumoral Heterogeneity and Clonal Evolution Induced by HPV Integration" (pacBio)

  Dataset EGAD00001009631

• Dataset for "Intratumoral Heterogeneity and Clonal Evolution Induced by HPV Integration" (ONT)

  Dataset for "Intratumoral Heterogeneity and Clonal Evolution Induced by HPV Integration" (ONT)

  Dataset EGAD00001009632

• Whole exome sequencing data for paired non-serous endometrial and ovarian carcinomas from 27 patients with concurrent tumours.

  Dataset for Synchronous Endometrial and Ovarian Cancer

  Dataset EGAD00001015680

• Linnarsson lab general data access committe

  Committee that handles the majority of policies for the Linnarsson Lab at Karolinska Institutet

  Dac EGAC50000000835

• Use of Deep Sequencing to Dectect Clonal Mutations In Sun Exposed Skin Epidermis

  This study aims to define the landscape of somatic mutations in sun exposed human skin by deep sequencing, analyse their frequency and use the data to infer the effect of mutations on proliferating cell behaviour. The frequency of each mutation will reflect the size of the clone of cells in the tissue sample. By analyzing small samples, clones with as few as 100 cells will be detectable. Allele frequency distributions for each mutation will be used to infer cell fate using published methods (Klein et al. 2010). This study will shed unprecedented light on the early clonal events that lead to the emergence of cancer.

  Dataset EGAD00001001090

• Prostate_Cancer_Whole_Genome_Validations

  We propose to definitively characterise the somatic genetics of Prostate cancer through generation of comprehensive catalogues of somatic mutations by high coverage genome sequencing. This study will aim to validate the findings of the whole genome study by re-sequencing regions of interest using a bespoke pulldown bait. See ICGC website for more information: http://icgc.org/icgc/cgp/70/508/71331

  Study EGAS00001000427

• cell-free Methylated DNA by Immunoprecipitation and Sequencing (cfMeDIP) of human meningioma samples.

  Raw data for cell-free Methylated DNA by Immunoprecipitation and Sequencing (cfMeDIP) of human meningioma samples.

  Study EGAS50000001539

• Whole-genome sequencing for 61 early-onset diabetes patients and 174 controls

  This dataset contains 241 paired FASTQ files for 61 early-onset diabetes patient and 174 controls sequenced with MGI Tech DNBSEQ-T10 and DNBSEQ-T7.

  Dataset EGAD50000001450

• Chip-exo and Chip-nexus for five TFs in three colorectal cancer cell lines

  Chip-exo and Chip-nexus for FOXA1, HNF4A, KLF5, MYC, and TCF7L2 in colorectal cancer cell lines LoVo, GP5D, COLO320DM

  Dataset EGAD00001004099

• Dac for "Combined single-cell transcriptomics and T-cell receptor sequencing reveal heterogeneity of mycosis fungoides between and within patients and identify a CD4+ cytotoxic subtype"

  Dac for "Combined single-cell transcriptomics and T-cell receptor sequencing reveal heterogeneity of mycosis fungoides between and within patients and identify a CD4+ cytotoxic subtype" with Name: Menghong Yin Email address: menghong.yin@dkfz-heidelberg.de Associated affiliation: Translational Skin Cancer Research Lab (DKFZ)

  Dac EGAC50000000168

• Integrative understanding of human immune system by functional genomics and development of intervention strategies for the prevention of autoimmune diseases

  Various peripheral blood immune cell subsets from 39 healthy volunteers and 50 rheumatoid (RA) donors were collected ("CD16p_Mono", "CL_Mono???, "DN_B", "Fr_II_eTreg???, "mDC???, "Mem_CD4" , "Naive_B" , "Naive_CD4" , ???Neu", "NK" , "pDC" , "Plasmablast", ???SM_B", "Tfh", "Th1", "Th17", "Th2" , "USM_B"). 15 RA patients were analyzed longitudinally. RNA-seq was performed with each immune cell subset samples. After gene expression quantification samples were filtered.

  Study JGAS000598

• Age-specific nasal epithelial responses to SARS-CoV-2 infection : GEX

  In this study, we investigate differences in the cellular landscape and functionality of ex vivo cultured nasal epithelial cells in response to SARS-CoV-2 infection across different age groups: paediatric (<12y), adult (30-50y), and older adults (>70y). We unravel, that while ciliated cells serve as primary sites for viral replication consistently across all age groups, a distinctive goblet inflammatory subtype emerges in infected paediatric cultures, characterized by heightened expression of interferon-stimulated genes and incomplete viral replication. Conversely, older adult cultures infected with SARS-CoV-2 exhibit a proportional surge in basaloid-like cells, which not only facilitate viral dissemination but also demonstrate associations with altered epithelial repair pathways.

  Dataset EGAD00001015345

• cfRRBS methylation profiling of cfDNA from cerebrospinal fluid from pediatric CNS tumor patients

  In this study, we explore the potential of classifying pediatric brain tumors based on methylation profiling of the cell-free DNA in cerebrospinal fluid (CSF). For this proof-of-concept study, we collected 20 cerebrospinal fluid samples of pediatric brain cancer patients via a ventricular drain placed for reasons of increased intracranial pressure. For 11 patients in this study we collected matched tumor DNA. This cohort contains fastQ files of cfRRBS data of these samples.

  Dataset EGAD50000000554

• DAC anti-MPO BCR sequences

  DAC for the requests of access to data of anti-MPO BCR sequences in the EGA repository,

  Dac EGAC50000000446

• NGS WGS Data - Unic TDP

  WGS data from the Unicorn-PASS cohort for the Tandem Duplicator Phenotype paper

  Dataset EGAD50000001567

• Integrative genomic profiling of large-cell neuroendocrine carcinomas reveals distinct subtypes of high-grade neuroendocrine lung tumors

  Large-cell neuroendocrine lung carcinomas (LCNEC) have similarities with other lung cancers, but their precise relationship has remained unclear. We conducted comprehensive genomic (n=60) and transcriptomic (n=69) analyses of 75 LCNECs and identified two molecular subgroups: “type I LCNECs” with bi-allelic TP53 and STK11/KEAP1 alterations (37%), and “type II LCNECs” enriched for bi-allelic inactivation of TP53 and RB1 (42%). Despite sharing genomic alterations with adenocarcinomas and squamous cell carcinomas, no transcriptional relationship was found; instead LCNECs form distinct transcriptional subgroups with closest similarity to SCLC. While type I LCNECs and SCLCs exhibit a neuroendocrine profile with ASCL1high/DLL3high/NOTCHlow, type II LCNECs bear TP53 and RB1 alterations and differ from most SCLC tumors with reduced neuroendocrine markers, a pattern of ASCL1low/DLL3low/NOTCHhigh and upregulation of immune-related pathways. In conclusion, LCNECs are comprised of two molecularly defined subgroups, and distinguishing them from SCLC may allow for stratified targeted treatments for high-grade neuroendocrine lung tumors.

  Study EGAS00001000708

• WES and WGS data for HGSC patient derived cell lines and fresh frozen tumor samples from same patients

  Sequencing data for three HGSC patients with patient derived cell lines. WES data for two patient derived cell line samples and matched blood control samples. Fresh frozen tumor samples of two patients with WES or WGS sequencing data.

  Dataset EGAD00001009330

• Organoid Derivation Project - GRCh38 - RNAseq (2023-06-22)

  Sequencing of tissue samples and their derived organoids from oesophageal, pancreatic and colorectal cancer patients. . This dataset contains all the data available for this study on 2023-06-22.

  Dataset EGAD00001011092

• TXT_Cytof_15B

  Matrix of normal values from 39 marker CyTOF assay performed on longitudinal BMMC. FCS files from the CyTOF assay were normalized and concatenated using Fluidigm's CyTOF software and then de-multiplexed using Astrolabe Diagnostics, Inc., a commercial, cloud-based platform for single-cell analysis.

  Dataset EGAD00001011143

• SNF_CyTOFF_20

  Matrix of normal values from 39 marker CyTOF assay performed on baseline BMMC. FCS files from the CyTOF assay were normalized and concatenated using Fluidigm's CyTOF software and then de-multiplexed using Astrolabe Diagnostics, Inc., a commercial, cloud-based platform for single-cell analysis.

  Dataset EGAD00001011146

• UCSF Pediatric Bithalamic Glioma Genome Project

  Targeted next-generation sequencing of 13 pediatric bithalamic diffuse gliomas. BAM files of targeted next-generation DNA sequencing data of 13 pediatric gliomas, with multi-region sequencing data from 2 of these cases (17 total tumor samples). Genomic DNA was extracted from formalin-fixed, paraffin-embedded blocks of tumor tissue from using the QIAamp DNA FFPE Tissue Kit (Qiagen). Capture-based next-generation DNA sequencing was performed at the University of California, San Francisco Clinical Cancer Genomics Laboratory, using an assay that targets all coding exons of 480 cancer-related genes, select introns of 47 genes, and TERT promoter with a total sequencing footprint of 2.8 Mb (UCSF500 Cancer Panel). Sequencing libraries were prepared from genomic DNA, and target enrichment was performed by hybrid capture using a custom oligonucleotide library (Nimblegen SeqCap EZ Choice). Captured libraries were sequenced as paired-end 100 bp reads on an Illumina HiSeq 2500 instrument. Duplicate sequencing reads were removed computationally to allow for accurate allele frequency determination and copy number calling.

  Dataset EGAD00001005499

• Data of the Institute of Pathology, University Medical Center Freiburg, Germany

  DAC for proteomics data deposited in EGA by the proteomics laboratory of the Institute of Pathology, University Medical Center Freiburg, Germany

  Dac EGAC50000000048